Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Benthic organisms (1)
- Cell metabolism (1)
- Chlorophyll (1)
- Disease classification (1)
- Dissolved oxygen (1)
-
- Effluent quality (1)
- Freshwater phytoplankton (1)
- Geometric Build-up (GBU) Solution (1)
- Information theory (1)
- Limnology (1)
- Mass spectrometry (1)
- Mathematical modeling of protein structure (1)
- Molecular Distance Geometry Problem (MDGP) (1)
- Molecular communication (1)
- PH (1)
- Prostate cancer (1)
- Serum (1)
- Statistical analysis (1)
- Unigenic evolution (1)
- Water analysis (1)
- Water temperature (1)
- Zooplankton (1)
Articles 1 - 5 of 5
Full-Text Articles in Applied Mathematics
End-To-End Molecular Communication Channels In Cell Metabolism: An Information Theoretic Study, Zahmeeth Sayed Sakkaff, Jennie L. Catlett, Mikaela Cashman, Massimiliano Pierobon, Nicole R. Buan, Myra B. Cohen, Christine A. Kelley
End-To-End Molecular Communication Channels In Cell Metabolism: An Information Theoretic Study, Zahmeeth Sayed Sakkaff, Jennie L. Catlett, Mikaela Cashman, Massimiliano Pierobon, Nicole R. Buan, Myra B. Cohen, Christine A. Kelley
Department of Biochemistry: Faculty Publications
The opportunity to control and fine-tune the behavior of biological cells is a fascinating possibility for many diverse disciplines, ranging from medicine and ecology, to chemical industry and space exploration. While synthetic biology is providing novel tools to reprogram cell behavior from their genetic code, many challenges need to be solved before it can become a true engineering discipline, such as reliability, safety assurance, reproducibility and stability. This paper aims to understand the limits in the controllability of the behavior of a natural (non-engineered) biological cell. In particular, the focus is on cell metabolism, and its natural regulation mechanisms, and …
Geometric Build-Up Solutions For Protein Determination Via Distance Geometry, Robert Tucker Davis
Geometric Build-Up Solutions For Protein Determination Via Distance Geometry, Robert Tucker Davis
Masters Theses & Specialist Projects
Proteins carry out an almost innumerable amount of biological processes that are absolutely necessary to life and as a result proteins and their structures are very often the objects of study in research. As such, this thesis will begin with a description of protein function and structure, followed by brief discussions of the two major experimental structure determination methods. Another problem that often arises in molecular modeling is referred to as the Molecular Distance Geometry Problem (MDGP). This problem seeks to find coordinates for the atoms of a protein or molecule when given only a set of pair-wise distances between …
Development Of An Unbiased Statistical Method For The Analysis Of Unigenic Evolution, Colleen D. Behrsin, Chris J. Brandl, David W. Litchfield, Brian H. Shilton, Lindi M. Wahl
Development Of An Unbiased Statistical Method For The Analysis Of Unigenic Evolution, Colleen D. Behrsin, Chris J. Brandl, David W. Litchfield, Brian H. Shilton, Lindi M. Wahl
Biochemistry Publications
Background: Unigenic evolution is a powerful genetic strategy involving random mutagenesis of a single gene product to delineate functionally important domains of a protein. This method involves selection of variants of the protein which retain function, followed by statistical analysis comparing expected and observed mutation frequencies of each residue. Resultant mutability indices for each residue are averaged across a specified window of codons to identify hypomutable regions of the protein. As originally described, the effect of changes to the length of this averaging window was not fully eludicated. In addition, it was unclear when sufficient functional variants had been examined …
Computational Protein Biomarker Prediction: A Case Study For Prostate Cancer, Michael Wagner, Dayanand N. Naik, Alex Pothen, Srinivas Kasukurti, Raghu Ram Devineni, Bao-Ling Adam, O. John Semmes, George L. Wright Jr.
Computational Protein Biomarker Prediction: A Case Study For Prostate Cancer, Michael Wagner, Dayanand N. Naik, Alex Pothen, Srinivas Kasukurti, Raghu Ram Devineni, Bao-Ling Adam, O. John Semmes, George L. Wright Jr.
Mathematics & Statistics Faculty Publications
Background: Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates.
Results: Thorough cross-validation studies and randomization tests are performed on a prostate cancer dataset with over 300 patients, obtained …
A Mathmatical Model Of Primary Productivity And Limnological Patterns In Lake Mead, Lorne G. Everett
A Mathmatical Model Of Primary Productivity And Limnological Patterns In Lake Mead, Lorne G. Everett
Publications (WR)
The temporal and spatial changes in chemical and biological properties of Lake Mead have been investigated, thereby indicating the sources of water pollution and the time of highest pollution potential. Planktonic organisms have been shown to indicate the presence of water problems. Macro- and micro-nutrient analyses have shown that primary productivity is not inhibited by limiting concentrations. A mathematical model has been developed, tested with one set of independent data, and shown worthy of management utility. Although the model works very well for the Lake Mead area, the physical reality of the Multiple Linear Regression equation should be tested on …